Metadata Standards for Web-based Resources

Editor: Peiya Liu
Siemens Corporate Research
Standards
Metadata Standards for
Web-Based Resources
Achim Steinacker
University of
Technology,
Darmstadt
Amir Ghavam
University of
Ottawa
Ralf Steinmetz
German National
Research Center for
Information
Technology
O
ne of the main reasons for the Web’s success
is that it lets us provide information to millions of people. We can integrate information
already available somewhere on the Web in our
own pages by just adding a link. However, finding
relevant information has become more difficult.
Search engines usually offer thousands of query
results if the user provides popular or generic keywords. The problem is that it’s still not possible to
describe HTML-page or multimedia content adequately. Data about the information in a resource,
also called metadata, can allow the proper search
and processing of Web pages.1 Metadata shifts the
description of the content from the string-matching level, where you can’t make decisions about a
resource’s relevance, to a conceptual level, where
users can semantically describe what they is actually looking for.
Consider the following definition of
multimedia:
Metadata
We can define metadata as information about
information. Librarians have used it for hundreds
of years. In fact, a library catalog, which helps
librarians manage their books and journals, is a
popular example of metadata use. Users search
these catalogs for material about a particular subject and find information on the library shelves.
Search engines like Yahoo are using catalogs to
structure Web page content. If there’s no information available about the resource, it’s impossible to classify it other than by manually reviewing
it and deciding where to list it in the catalog. Having information about the content, author, or
legal conditions makes it easier for humans and
computers to classify a resource. Metadata can be
useful for
❚ summarizing the meaning of the data,
❚ allowing users to search for the data,
A multimedia system is characterized by computercontrolled, integrated production, manipulation,
presentation, storage, and communication of
independent information, which is encoded at
least through a continuous and a discrete medium.2
This suffices from a technical point of view, and
it helps people understand how to define and
build a multimedia system. What’s missing is how
to describe what’s inside a multimedia resource,
what it’s good for, and who can or should use it
and why. We need a description of the content of
multimedia resources available on the Web, tailored to specific needs of different users. The
Dublin Core, a simple metadata element set for
Web resources, and the Learning Object Metadata Scheme by the IEEE Working Group P1484.12
are two examples of metadata schemes that
describe multimedia resources. (See the “Web
Resources” sidebar for more information.)
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1070-986X/01/$10.00 © 2001 IEEE
❚ allowing users to determine if the data is what
they want,
❚ giving information that affects the use of data
(legal conditions, size, age, and so on), and
❚ indicating relationships with other resources.3
To use and benefit from metadata on the Internet, we need a common format for expressing it
that should be designed for machines rather than
humans. Merging the web of human-readable
documents with a network of machine-understandable metadata promises immense potential.4
Proxy caches, Web browsers, search engines, and
other Web tools can then work better with
humans and participate more intelligently in
locating, evaluating, accessing, and managing
Web resources.
Metadata application and syntax
The first step in describing a resource with
metadata is choosing an appropriate metadata element set and an appropriate vocabulary as values
for the elements. Often the vocabulary for a metadata scheme comes from an existing ontology
that describes knowledge in general—for example,
the International Standard ISO/IEC 11179: Information technology, specification, and standardization of data elements.
Although we’ve developed every element set
and scheme to find and manage resources, choosing a scheme depends on the resource’s target
group. For example, the type and number of
metadata descriptions a librarian needs to catalog
a video is completely different from those a company needs to manage a Web portal of self-learning videos, even though they might be describing
the same multimedia resource. Therefore, different metadata descriptions for the same resource
exist.
One simple metadata scheme—conceived for
author-generated descriptions of Web resources—
is the Dublin Core. (Another possible metadata
scheme, especially for videos, is MPEG-7.5) The
Dublin Core facilitates the discovery of online
resources in a networked environment. The current metadata set consists of 15 elements. It’s
completely text oriented and, therefore, human
readable. Each element is repeatable and optional, and the entire set is extensible.6 The 15 categories of the Dublin Core are
❚ title,
❚ author or creator,
❚ subject and keywords,
❚ description,
❚ publisher,
❚ other contributors,
❚ resource type,
❚ format,
ARIADNE Consortium: http://ariadne.unil.ch
IMS Project: http://www.imsproject.org
Learning Object Metadata Scheme: http://ltsc.ieee.org/doc/wg12/
LOM_WD5.pdf
Learning Object Metadata Working Group: http://ltsc.ieee.org/wg12/
index.html
LOM-Editor from KOM, TU Darmstadt: http://www.multibook.de/lom
LRN 2.0 Toolkit, Microsoft: http://www.microsoft.com/elearn
❚ language,
❚ relation,
❚ coverage, and
❚ rights management.
Depending on the element set, we can apply
metadata to a resource in different ways. Metadata
can be within the resource itself—for example, as
digital watermarks in pictures or videos that protect a resource’s integrity or ensure its authorship—
as HTML metatags, or in a separate description file.
When including the metadata description
within the resource, the syntax of the resource
gives the syntax and encoding for the metadata.
HTML metatags are a simple way to apply metadata to a Web-based document. The following
example shows Dublin Core encoded at the beginning of an HTML page with metatags. In this case,
the metadata describes a Java applet used for visualization of communication protocols in an Ethernet local area network.
<META NAME=“DC.Title” CONTENT=“Ethernet Applet”>
<META NAME=“DC.Description”
CONTENT=“Visualization of Carrier
Sense Multiple Access Protocol with
Collision Detection (CSMA/CD) IEEE
802.3 (Ethernet)”>
<META NAME=“DC.Type” CONTENT=“Learning
Material”>
<META NAME=“DC.Format” CONTENT=“Java
Applet”>
<META NAME=“DC.Relation.References”
CONTENT=“http://www.multibook.de/et
hernet.htm”>
January–March 2001
❚ date,
Web Resources
❚ resource identifier,
❚ source,
The disadvantage of this approach is that it’s
impossible to change parts of the metadata
71
Standards
RDF offers a way to publish
human-readable and
machine-processable
vocabularies designed to
encourage the reuse and
extension of metadata
semantics among disparate
information communities.
description without accessing the resource. The
other problem is duplication of information. The
DC.Title attribute’s value will most likely appear
again in the HTML Title tag. Using semantic
annotation languages like HTMLa to include
metadata within the resource overcomes this
problem, but they have other drawbacks.7
If we store and deliver the description separately from the resource, how do we encode the
descriptions? Although almost as many possibilities for encoding metadata exist as there are metadata schemes, we can store almost every metadata
scheme as an XML file. Unfortunately, using XML
and a document type definition (DTD) to describe
a metadata scheme only lets us check a description’s syntax. We can’t use them to specify what
the description elements mean. One approach
aimed at getting closer to the meaning of descriptions is the World Wide Web Consortium’s
Resource Description Framework (RDF).8
RDF
IEEE MultiMedia
RDF permits encoding, exchanging, and
reusing structured metadata. It provides the basic
requirements for metadata interoperability across
different resource description communities and
applications. RDF builds on the XML syntax and
imposes needed structural constraints to express
semantics. Plus, it offers a way to publish humanreadable and machine-processable vocabularies
designed to encourage the reuse and extension of
metadata semantics among disparate information
communities.
72
RDF is based on a concrete formal model that
uses directed graphs for representing the semantics of metadata. Basicly, a collection of properties,
or an RDF description, describes a resource. Each
of these properties has a property type and value.
The RDF model builds on the triple relationship
of resource, property, and value—in other words,
subject, predicate, and object. We can use the Ethernet applet we mentioned earlier as an example.
In this model, the applet is the resource, DC.Type
is a property of this resource, and Learning
Material is the value of this property. The corresponding RDF–XML syntax for this example is
<?xml version = “1.0”?>
<rdf:RDF
xmlns:rdf=“http://www.w3.org/1999/0
2/22-rdf-syntax-ns#”xmlns:DC=
“http://metadata.net/dstc/DC-10EN/#”>
<rdf:Description xml:lang=“en” about=“
http://www.multibook.de/EthernetApplet.html “>
<DC:Title>Ethernet Applet</DC:Title>
<DC:Description>Visualization of
Carrier Sense Multiple Access Protocol with Collision Detection
(CSMA/CD) IEEE 802.3(Ethernet)
</DC:Description>
<DC:Type>Learning Material</DC:Typer>
<DC:Format>Java Applet</DC:Format>
<DC.Relation.References>http://www.mu
ltibook.de/ethernet.htm</DC:Relatio
n.References>
</rdf:Description>
</rdf:RDF>
RDF uses the W3C’s namespace convention. In
this example, we declare both the RDF and Dublin
Core schemes as namespaces and abbreviate them
as RDF and DC, respectively. The Uniform
Resource Identifiers associated with these namespaces refer to the related schemes. Using them,
we can access the necessary vocabularies for each
data model. The element <rdf:RDF> is a wrapper
that marks the boundaries in an XML document
where the content is explicitly intended to be
mapped into an RDF data model instance. The element <rdf:Description> contains the URI of
the resource in its about statement. The element
<DC:Type> in the context of the description represents a property-type DC:Type and a value of
Learning Material.
While XML specifies a description’s syntax,
RDF tries to structure the meaning of the descriptions’ elements. An RDF description provides
answers to questions like, what is the statement
about, who says it, and where is it stored? Like
XML, it also doesn’t provide answers to the question, what is the meaning of the statement? To
answer this question, we must agree on a shared
vocabulary or namespace about the statements.
Without using a vocabulary, it’s impossible to
automatically make decisions about the resource.
Therefore, the W3C is currently developing the
RDF Schema.9
The RDF Schema introduces a basic vocabulary
for a statement’s meaning in a metadata description
and for the relation between two metadata descriptions. Although the vocabulary in the RDF Scheme
is currently limited, it builds the bridge between
metadata descriptions such as the Dublin Core and
formal semantic descriptions of specific domains
called ontologies. Ontologies using description languages like the Ontology Interchange Language
(OIL)10—where the concepts of the ontology can be
encoded with the RDF Schema—can be connected
with a metadata description of a Web-based
resource also encoded with the RDF Schema. The
combination of semantic networks or ontologies
with descriptions of Web-based resources will eventually lead to the so-called Semantic Web.11
LOM
The purpose of the Learning Object Metadata specification (http://ltsc.
ieee.org/doc/wg12/LOM_WD5.pdf) is to
❚
enable learners or instructors to search, evaluate, acquire, and use learning objects.
❚ enable the sharing and exchange of learning objects across any technology-supported learning system
❚ enable the development of learning objects in units that can be combined
and decomposed in meaningful ways
❚ enable computer agents to automatically and dynamically compose personalized lessons for an individual learner
❚ complement the direct work on standards that focus on enabling multiple
learning objects to work together within an open, distributed learning
environment.
❚ enable, where desired, the documentation and recognition of the completion of existing or new learning and performance objectives associated with learning objects
❚ enable a strong and growing economy for learning objects that supports
and sustains all forms of distribution whether for profit or not
❚ enable education, training and learning organizations—both government,
public and private—to express educational content and performance
standards in a format separate from the content
❚ provide researchers with standards that support the collection and sharing of comparable data concerning the applicability and effectiveness of
learning objects
❚ define a simple yet, extensible standard for multiple domains and jurisdictions so it can be broadly adopted and applied
❚ support necessary security and authentication for the distribution and use
of learning objects
ogy-supported learning. Examples of such applications include computer-based training systems,
interactive learning environments, intelligent
computer-aided instruction systems, distance
learning systems, Web-based learning systems, and
collaborative learning environments. Examples of
learning objects include multimedia content,
instructional content, instructional software, and
software tools referenced during technologysupported learning. In a wider sense, learning
objects could even include learning objectives,
January–March 2001
Universities and many other organizations
need to manage, find, and reuse learning materials, so describing resources with appropriate metadata could be particularly useful. One of the most
promising metadata approaches for describing
learning resources was developed by the IEEE
Working Group P1484.12: the Learning Object
Metadata (LOM) Scheme. (See the sidebar “LOM’s
Purpose.”) It’s mainly influenced by the work of
the Educom’s Instructional Management Systems
project and Alliance of Remote Instructional
Authoring and Distribution Networks for Europe,
or the ARIADNE Consortium. There are already
editors available and companies like Microsoft
have started to offer free software for it (See the
“Web Resources” sidebar for more information).
The LOM scheme uses almost every category of
the Dublin Core and extends it with categories
and attributes tailored to the needs of learners and
authors searching the Web for material.
The LOM approach specifies the syntax and
semantics of learning object metadata. A learning
object is any entity, digital or nondigital, which
can be used, reused, or referenced during technol-
LOM’s Purpose
73
Standards
❚ Category 1. General, regroups all the resource’s
context-independent features.
❚ Category 2. Lifecycle, regroups the features
linked to the resource’s lifecycle.
❚ Category 3. Meta-metadata, regroups the features of the description itself (rather than those
of the resource being described).
❚ Category 4. Technical, regroups the resource’s
technical features.
❚ Category 5. Educational, regroups the
resource’s educational and pedagogic features.
❚ Category 6. Rights, regroups the resource’s conditions of use.
Figure 1. A modular learning resource, its Learning Object Metadata
description with RDF, and a visualization of the resource including relations to
other resources.
people, organizations, or events. The IEEE LOM
standard should conform to, integrate with, or reference open standards and existing work in related
areas.
The definition of LOM divides the descriptors
of a learning object into categories. The version of
this proposal issued on 11 November 2000
(http://ltsc.ieee.org/wg12/index.html) introduces
nine categories:
Interactivity type
❚ Category 9. Classifications, allows for
description of the resource’s characteristic by
entries in classifications
Taken together, these categories form the Base
Scheme. For example, Figures 1 through 4 show
the detailed structure of the technical and educational categories. Some elements like the Descrip-
Specific kind of resource
Interactivity level
Learning context ( unordered list, eight items)
Level of interactivity between an end user and the resource
The typical kind of learners
Semantic density
Intended end user role (ordered list, four items)
LOM: Educational
Difficulty
How hard it is to work through the resource
Descripton
Comments on how the resource is used
Figure 2. Educational category of the Learning Object Metadata scheme.
74
❚ Category 8. Annotation, allows for comments
on the educational use of the resource.
Learning resource type (ordered list, eight items)
The type of interactivity supported by the resource
Usefulness of the resource compared to its size of duration
❚ Category 7. Relation, regroups features of the
resource that link it to other resources.
Normal user of the resource
Typical age range (unordered list, four items)
Age of the typical intended user
Typical learning time
Typical time it takes to work with the resource
Format (unordered list, eight items)
Location (ordered list, eight items)
Technical data type of the resource
A location of the resource
Duration
Type
Time a resource takes when played in seconds
LOM: Technical
Requirements
(unordered list, eight items)
Name
Needs to access the resources
Minimum version
Maximum version
Size
The size of the digital resource bytes
Installation remarks
Description of how to install the resource
tion element of the General category allow free
text as values, while for other elements the values
are restricted to a limited vocabulary.
Like the Dublin Core, all categories are optional in the LOM scheme. If we want to use all categories and attributes from LOM, we must fill out
at least 60 fields. An authoring system can automatically fill in entries such as author, creation
date, and keywords, but there are still many
entries left that users must fill in. Many people
consider the time needed to describe all a
resource’s properties will prevent a metadata
scheme from being widely distributed and used.
Another problem with using a general scheme
like LOM are special attributes—for example, the
difficulty level (category 5, educational) should be an integer between
0 and 4. It seems almost impossible
to find a value for difficulty that’s
valid in diverse societies and institutions all over the world, even if you
can specify a target group with the
values of other attributes. Furthermore, a resource’s difficulty level
depends on the existing knowledge
of the user and the context in which
the resource is used.
It’s unlikely that a single LOM
description will be able to make
statements about a complex educational resource. Using modular
learning resources to build individual lessons automatically requires
more information than the descrip-
Other platform requirements
Information about other hardware and software requirements
tion of a single resource can provide. Categories
with no educational background also have this
problem, and the rights management category
doesn’t provide enough information to manage
a resource within a commercial scenario. LOM
tries to reduce the needs from all areas of computer-supported learning to a common denominator. It can’t and it isn’t meant to provide all
information for every scenario. All categories are
optional, and users can easily extend the Base
Scheme to fit particular needs. LOM is just the
common starting point of a growing user community including companies and scientific projects, to share and reuse their existing learning
materials and knowledge.
Figure 3. Technical
category of the Learning
Object Metadata
scheme.
Figure 4. Screen shot of
an editor for describing
and managing Learning
Object Metadata
descriptions.
75
Standards
Conclusion
One problem with all metadata approaches is
that they try to be specialized and generic, so they
are useful for different scenarios. While the
languages for encoding and exchanging the
metadata are already available, it will take more
time for the industry to agree on a shared
vocabulary for the metadata elements and values.
Another problem with metadata is supporting
all the different user roles that are involved during
a resource’s production and distribution. Future
authoring systems will be able to automatically
generate many metadata values and will offer userfriendly ways to provide information without
dealing with the encoded metadata directly. Future
work in this area will focus on building semantic
networks out of single metadata descriptions. Even
for the authors of a resource, it is not always easy to
provide the adequate information. Establishing a
network of resources without being an expert in
knowledge building is even harder without
appropriate tools that hide the complexity of the
underlying models.
MM
References
IEEE MultiMedia
1. W3C, “Metadata Activity Statement”; http://www.
w3.org/Metadata/Activity.html.
2. R. Steinmetz and K. Nahrstedt, Multimedia. Computing Communications & Applications, 2nd ed., Prentice
Hall, Upper Saddle River, N.J., 1999.
3. R. Ianelle and A. Waugh, “Metadata: Enabling the
Internet,” http://www.dstc.edu.au/RDU/pres/
cause97/sld001.htm.
76
4. T. Berner Lee, “Realising the Full Potential of the
Web,” http://www.w3.org/1998/02/Potential.html.
5. F. Nack and A.T. Lindsay, “Everything You Wanted
to Know About MPEG-7.1: Part 1,” IEEE MultiMedia,
vol. 6, no. 3, July–Sept. 1999, pp. 65-77.
6. Dublin Core Metadata Initiative, Dublin Core Metadata Element Set, Version 1.1, http://purl.org/DC/documents/rec-dces-19990702.htm.
7. S. Decker et al., “Ontobroker: Ontology-Based
Access to Distributed and Semi-Structured Information,” Semantic Issues in Multimedia Systems. Proc.
DS-8, Kluwer Academic, Boston, 1999, pp. 351-369.
8. W3C, “Resource Description Framework (RDF)
Model and Syntax Specification.” Feb. 1999,
http://www.w3.org/TR/REC-rdf-syntax.
9. W3C, “Resource Description Framework (RDF)
Schema Specification 1.0”, Mar. 2000,
http://www.w3.org/TR/2000/CR-rdf-schema20000327.
10. I. Horrocks et al., The Ontology Interchange Language
OIL, tech report, Free Univ. of Amsterdam, 2000,
http://www.ontoknowledge.org/oil.
11. S. Decker et al., “The Semantic Web: The roles of
XML and RDF,”: IEEE Internet Computing; vol. 4, no.
5, Sept./Oct. 2000, pp. 63-74.
Readers may contact Steinacker at KOM, Darmstadt, University of Technology, Merckstr.25, 64283
Darmstadt, Germany, email stein@kom.tu-darmstadt.de.
Contact Standards editor Peiya Liu, Siemens Corporate Research, 755 College Road East, Princeton, NJ
08540, email pliu@scr.siemens.com.